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Heavy metal pollution has been a global concern and key points of environmental pollution prevention and control due to the growing problems of urbanization and industrialization. Rapidly and correctly apportioning sources of heavy metal is still a great challenge because of the stability of source fingerprint and complex interaction of multiple contaminants and sources. In this study, we perform a combination of optimization of pollution source fingerprint and source apportionment through jointly utilizing two machine classification and screening methods for characterizing the pollution sources of heavy metal in the sediments of an urban river and its surrounding soils. Dominance-based rough set model (DRS), content optimization tools, and multivariate curve resolution-alternating least squares model (MCR-WALS) were employed to screen representative pollution source samples, optimize pollution source fingerprint, and apportion the potential sources of heavy metals, respectively. Further, Support vector machine (SVM) was adopted to correspondence analysis results and pollution fingerprint based on the factor characteristics for achieving source apportionment accurately. Results showed that the pollution source pollution source fingerprints optimized by DRS and optimization tools are more representative and stable, and the results obtained by SVM and MCR-WALS are more accurate comparing with traditional methods. As whole, source apportionment suggested that printing and dyeing, chemical, electroplating, metal processing were the main origins of heavy metals in this area and the proportions of them in sediment and soil pollution sources were 67.05% and 28.43%, respectively. Besides, coal combustion was also the main sources of heavy metal pollution in soils, accounting about 34.16%. Results of the study can advance our knowledge to better understand the characterization of heavy metal pollution in the peri-urban ecosystem and to design effective targeted strategies for reducing heavy metal pollution diffusion. [Display omitted] • A combination of fingerprint screening and source apportionment was performed. • Characteristics and source-sink relationship of heavy metals in the river-soil system was studied. • Source apportionment was executed using MLR-WALS combined with SVM. • Multiple complex industrial activities were the dominant same type contributor of heavy metals in the river sediments. [ABSTRACT FROM AUTHOR]

Heavy metals (HMs) in lake sediments have aroused long-term attention due to their persistent threat to the lake ecosystems. Study into the pollution characteristics and potential sources of HMs in lakes, especially those heavily influenced by human activities, can give some insights to prevent and control the environmental risks of HMs. Lake Tai is the China's third largest freshwater lake but has been a drastic example of water pollution in recent decades. Here, we systematically investigated the characterization of pollution, risk and sources of HMs in the sediments of Lake Tai and its surrounding soils using several methods and tools. Specifically, a total of 46 sediments and 578 soils were collected from the study area, and geochemical approaches (geo-accumulation index and enrichment factor) and pollution indexes were jointly used to reveal the contamination characteristics of HMs. Meanwhile, the potential ecological risk index and probabilistic model of health risk assessment were employed to understand the environmental risk of HMs. Further, absolute principle component score-multiple linear regression and positive matrix factorization models were comparatively applied to apportion the sources of HMs. Results showed that various metals including Cd, Cr, As, Hg, Pb, and Cu appeared contamination level in varying degrees both in the sediments and soils. In particular, Cd, As and Hg were identified as the significant contaminants and presented moderate ecological risk. As a whole, the health risk levels of metals were acceptable. Source apportionment suggested that industrial discharge, agricultural activities, atmospheric deposition and natural source were the potential origins of HMs in this area. Among them, anthropogenic activities were the largest dominator of HMs with contribution of >75%. The study will advance our knowledge on HMs in lake and its surrounding soils and provide reference for policy maker to design migration strategies for protecting the lake ecosystems. Unlabelled Image • Contamination risk and sources of HMs in the sediments of Lake Tai were studied. • Cd, As and Hg were recognized as the significant contaminants. • Contamination risk of HMs in the sediments of Lake Tai was higher than surrounding soils. • Anthropogenic activities were the largest dominator of HMs with contributions of >75%. [ABSTRACT FROM AUTHOR]